Siem Logging
ancoleman/ai-design-components
Configure security information and event management (SIEM) systems for threat detection, log aggregation, and compliance.
Agent skill
Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigma --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .claude/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .claude/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigmaType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigma --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .agents/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .agents/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigma --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .cursor/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .cursor/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git --path skills/building-detection-rules-with-sigma--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigma --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .gemini/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .gemini/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigmaInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .github/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .github/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Anthropic-Cybersecurity-Skills building-detection-rules-with-sigma --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Anthropic-Cybersecurity-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/building-detection-rules-with-sigma .opencode/skills/building-detection-rules-with-sigma && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "building-detection-rules-with-sigma" agent skill from https://github.com/mukul975/Anthropic-Cybersecurity-Skills/tree/main/skills/building-detection-rules-with-sigma into .opencode/skills/building-detection-rules-with-sigma/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "building-detection-rules-with-sigma", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
building-detection-rules-with-sigmaBuilds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel.
Building Detection Rules With Sigma is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Use when creating portable detection logic from threat intelligence, mapping rules to MITRE ATT&CK techniques, or converting community Sigma rules into platform-specific queries using sigmac or pySigma backends.
Its SKILL.md is about 2.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `references/api-reference.md` and `scripts/agent.py`).
It sits in Security, covering Security operations and OSINT. It works with Splunk and Microsoft Sentinel. The repository describes itself as: 817 structured cybersecurity skills for AI agents · Mapped to 6 frameworks: MITRE ATT&CK, NIST CSF 2.0, MITRE ATLAS, D3FEND, NIST AI RMF & MITRE F3 (Fight Fraud) · agentskills.io…. The licence is Apache-2.0.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 54a7988. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pipgitFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
github.comattack.mitre.orgFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Building Detection Rules With Sigma loads about 2.7k tokens when it runs, and up to ~3.2k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 500 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from mukul975/Anthropic-Cybersecurity-Skills at commit 54a7988, republished under its Apache-2.0 licence (© mukul975). 500 words, ~2,658 tokens.
.claude/skills/building-detection-rules-with-sigma/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.Use this skill when:
Do not use for real-time streaming detection (Sigma is for batch/scheduled searches) or when the target SIEM has native detection features that Sigma cannot express (e.g., Splunk RBA risk scoring).
pySigma and appropriate backend (pySigma-backend-splunk, pySigma-backend-elasticsearch, pySigma-backend-microsoft365defender)git clone https://github.com/SigmaHQ/sigma.gitStart with a threat report or ATT&CK technique. Example: detecting Mimikatz credential dumping (T1003.001 — LSASS Memory):
title: Mimikatz Credential Dumping via LSASS Access
id: 0d894093-71bc-43c3-8d63-bf520e73a7c5
status: stable
level: high
description: Detects process accessing lsass.exe memory, indicative of credential dumping tools like Mimikatz
references:
- https://attack.mitre.org/techniques/T1003/001/
- https://github.com/gentilkiwi/mimikatz
author: mahipal
date: 2024/03/15
modified: 2024/03/15
tags:
- attack.credential_access
- attack.t1003.001
logsource:
category: process_access
product: windows
detection:
selection:
TargetImage|endswith: '\lsass.exe'
GrantedAccess|contains:
- '0x1010'
- '0x1038'
- '0x1fffff'
- '0x40'
filter_main_svchost:
SourceImage|endswith: '\svchost.exe'
filter_main_csrss:
SourceImage|endswith: '\csrss.exe'
filter_main_wininit:
SourceImage|endswith: '\wininit.exe'
condition: selection and not 1 of filter_main_*
falsepositives:
- Legitimate security tools accessing LSASS
- Windows Defender scanning
- CrowdStrike Falcon sensorUse sigma check to validate the rule:
# Install pySigma and validators
pip install pySigma pySigma-validators-sigmaHQ
# Validate rule
sigma check rule.ymlAlternatively, validate with Python:
from sigma.rule import SigmaRule
from sigma.validators.core import SigmaValidator
rule = SigmaRule.from_yaml(open("rule.yml").read())
validator = SigmaValidator()
issues = validator.validate_rule(rule)
for issue in issues:
print(f"{issue.severity}: {issue.message}")Convert to Splunk SPL:
from sigma.rule import SigmaRule
from sigma.backends.splunk import SplunkBackend
from sigma.pipelines.splunk import splunk_windows_pipeline
pipeline = splunk_windows_pipeline()
backend = SplunkBackend(pipeline)
rule = SigmaRule.from_yaml(open("rule.yml").read())
splunk_query = backend.convert_rule(rule)
print(splunk_query[0])Output:
TargetImage="*\\lsass.exe" (GrantedAccess="*0x1010*" OR GrantedAccess="*0x1038*"
OR GrantedAccess="*0x1fffff*" OR GrantedAccess="*0x40*")
NOT (SourceImage="*\\svchost.exe") NOT (SourceImage="*\\csrss.exe")
NOT (SourceImage="*\\wininit.exe")Convert to Elastic Query (Lucene):
from sigma.backends.elasticsearch import LuceneBackend
from sigma.pipelines.elasticsearch import ecs_windows_pipeline
pipeline = ecs_windows_pipeline()
backend = LuceneBackend(pipeline)
elastic_query = backend.convert_rule(rule)
print(elastic_query[0])Convert to Microsoft Sentinel KQL:
from sigma.backends.microsoft365defender import Microsoft365DefenderBackend
backend = Microsoft365DefenderBackend()
kql_query = backend.convert_rule(rule)
print(kql_query[0])Tag every rule with ATT&CK technique IDs in the tags field:
tags:
- attack.credential_access # Tactic
- attack.t1003.001 # Sub-technique
- attack.t1003 # Parent techniqueTrack detection coverage using the ATT&CK Navigator:
import json
# Generate ATT&CK Navigator layer from Sigma rules
layer = {
"name": "SOC Detection Coverage",
"versions": {"attack": "14", "navigator": "4.9", "layer": "4.5"},
"domain": "enterprise-attack",
"techniques": []
}
# Parse Sigma rules directory for technique tags
import os
from sigma.rule import SigmaRule
for root, dirs, files in os.walk("sigma/rules/windows/"):
for f in files:
if f.endswith(".yml"):
rule = SigmaRule.from_yaml(open(os.path.join(root, f)).read())
for tag in rule.tags:
if str(tag).startswith("attack.t"):
technique_id = str(tag).replace("attack.", "").upper()
layer["techniques"].append({
"techniqueID": technique_id,
"color": "#31a354",
"score": 1
})
with open("coverage_layer.json", "w") as f:
json.dump(layer, f, indent=2)Create test data and validate the rule catches the expected events:
# Use sigma test framework
sigma test rule.yml --target splunk --pipeline splunk_windows
# Or manually test in Splunk with sample data
# Upload Sysmon process_access log with known Mimikatz signatureValidate false positive rate by running against 7 days of production data in a non-alerting saved search.
Deploy the converted query as a scheduled search or correlation rule:
Splunk ES Correlation Search:
| tstats summariesonly=true count from datamodel=Endpoint.Processes
where Processes.process_name="*\\lsass.exe"
by Processes.src, Processes.user, Processes.process_name, Processes.parent_process_name
| `drop_dm_object_name(Processes)`
| where count > 0Elastic Security Rule (TOML format):
[rule]
name = "LSASS Memory Access - Credential Dumping"
description = "Detects suspicious access to LSASS process memory"
risk_score = 73
severity = "high"
type = "eql"
query = '''
process where event.action == "access" and
process.name == "lsass.exe" and
not process.executable : ("*\\svchost.exe", "*\\csrss.exe")
'''
[rule.threat]
framework = "MITRE ATT&CK"
[[rule.threat.technique]]
id = "T1003"
name = "OS Credential Dumping"Store rules in Git with automated testing:
# .github/workflows/sigma-ci.yml
name: Sigma Rule CI
on: [push, pull_request]
jobs:
validate:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- run: pip install pySigma pySigma-validators-sigmaHQ
- run: sigma check rules/
- run: sigma convert -t splunk -p splunk_windows rules/ > /dev/null| Term | Definition |
|---|---|
| Sigma | Vendor-agnostic detection rule format (YAML-based) that compiles to SIEM-specific queries via backends |
| pySigma | Python library replacing legacy sigmac for rule conversion, validation, and pipeline processing |
| Backend | pySigma plugin that translates Sigma detection logic into a target platform query language (SPL, KQL, Lucene) |
| Pipeline | Field mapping configuration that translates generic Sigma field names to SIEM-specific field names |
| Logsource | Sigma rule section defining the category (process_creation, network_connection) and product (windows, linux) of the target data |
| Detection-as-Code | Practice of managing detection rules in version control with CI/CD testing and automated deployment |
SIGMA RULE DEPLOYMENT REPORT
━━━━━━━━━━━━━━━━━━━━━━━━━━━
Rule ID: 0d894093-71bc-43c3-8d63-bf520e73a7c5
Title: Mimikatz Credential Dumping via LSASS Access
ATT&CK: T1003.001 - LSASS Memory
Severity: High
Status: Deployed to Production
Conversions:
Splunk SPL: PASS — Saved search "sigma_lsass_access" created
Elastic EQL: PASS — Detection rule ID elastic-0d894093 enabled
Sentinel KQL: PASS — Analytics rule deployed via ARM template
Testing:
True Positives: 4/4 test cases matched
False Positives: 2 in 7-day backtest (svchost edge case — filter added)
Performance: Avg execution 3.2s on 50M events/day© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 3 other files (scripts, references) in skills/building-detection-rules-with-sigma of mukul975/Anthropic-Cybersecurity-Skills.
Open the folder on GitHubat commit 54a7988
Building Detection Rules With Sigma next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Building Detection Rules With Sigma this skillmukul975/Anthropic-Cybersecurity-Skills | 34k | — | ~2.7k | Automated safety check: Pass | Apache-2.0 | |
| Siem Loggingancoleman/ai-design-components | 525 | — | ~3.4k | Automated safety check: Pass | MIT | |
| Threat Intel CampaignSCStelz/security-investigator | 249 | — | ~6.9k | Automated safety check: Pass | MIT | |
| Unified Secops Platformvinayaklatthe/microsoft-security-skills | 175 | — | ~2.1k | Automated safety check: Pass | MIT | |
| Siem Detectionbriiirussell/cybersecurity-skills | 413 | — | ~2.6k | Automated safety check: Notes | MIT | |
| Hunting Threatstrilwu/secskills | 157 | — | ~3.5k | Automated safety check: Pass | MIT |
ancoleman/ai-design-components
Configure security information and event management (SIEM) systems for threat detection, log aggregation, and compliance.
SCStelz/security-investigator
Turn a published threat-intelligence article into a tested threat-hunting campaign.
vinayaklatthe/microsoft-security-skills
Guidance for the Microsoft unified security operations platform that brings Microsoft Sentinel, Microsoft Defender XDR, Security Copilot, Threat Intelligence, and Microsoft Security Exposure…
briiirussell/cybersecurity-skills
Engineer and audit SIEM detection rules — log source coverage, Sigma / KQL / SPL / Elastic query authoring, MITRE ATT&CK mapping, false-positive tuning, and detection-as-code workflows.
trilwu/secskills
Run hypothesis-driven threat hunts across endpoint, network, cloud, and identity telemetry using stack counting, outlier analysis, and ATT&CK-based hypotheses, with SIEM query patterns for Splunk…
dandye/ai-runbooks
Enrich an IOC (IP, domain, hash, URL) with threat intelligence.
mukul975/Anthropic-Cybersecurity-Skills
Weighs infrastructure, TTP, malware code and timing evidence with the Diamond Model and competing hypotheses to reach a confidence-rated attribution.
mukul975/Anthropic-Cybersecurity-Skills
Walks through reverse engineering Go-compiled malware in Ghidra: parsing buildinfo and pclntab, recovering stripped function names and extracting dependencies.
mukul975/Anthropic-Cybersecurity-Skills
Guides forensic analysis of Windows LNK shortcut files and Jump Lists with LECmd, JLECmd and manual parsing to show file access and program execution.
mukul975/Anthropic-Cybersecurity-Skills
Hunts Windows malware persistence with Sysinternals Autoruns, covering run keys, services, scheduled tasks and drivers, with baseline comparison.
mukul975/Anthropic-Cybersecurity-Skills
Guides a Windows forensic examination of the NTFS Master File Table to recover deleted-file evidence, build timelines and spot timestomping.
mukul975/Anthropic-Cybersecurity-Skills
Detects DNS tunneling, ICMP exfiltration and HTTP-based covert channels in packet captures and DNS logs when hunting for hidden command-and-control traffic.
Works with
Categories
Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel. Building Detection Rules With Sigma is an agent skill from mukul975/Anthropic-Cybersecurity-Skills. Builds vendor-agnostic detection rules using the Sigma rule format for threat detection across SIEM platforms including Splunk, Elastic, and Microsoft Sentinel.
Building Detection Rules With Sigma fits situations like: creating portable detection logic from threat intelligence; mapping rules to MITRE ATT&CK techniques; converting community Sigma rules into platform-specific queries using sigmac; pySigma backends.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a claude-code`. Or copy the skill folder (skills/building-detection-rules-with-sigma in mukul975/Anthropic-Cybersecurity-Skills) into .claude/skills/building-detection-rules-with-sigma in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a codex`. Or copy the skill folder (skills/building-detection-rules-with-sigma in mukul975/Anthropic-Cybersecurity-Skills) into .agents/skills/building-detection-rules-with-sigma in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Anthropic-Cybersecurity-Skills --skill building-detection-rules-with-sigma -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-detection-rules-with-sigma, .gemini/skills/building-detection-rules-with-sigma, .github/skills/building-detection-rules-with-sigma and .opencode/skills/building-detection-rules-with-sigma in your project.
Going by SKILL.md and its folder, Building Detection Rules With Sigma needs Python for the scripts in its folder and the command-line tools its instructions call (pip and git). Our summary lists: Python 3.
SKILL.md names 2 domains. In commands or code: github.com and attack.mitre.org; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Building Detection Rules With Sigma is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.7k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 532 tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Building Detection Rules With Sigma: Siem Logging (ancoleman/ai-design-components, 525 stars), Threat Intel Campaign (SCStelz/security-investigator, 249 stars), Unified Secops Platform (vinayaklatthe/microsoft-security-skills, 175 stars) and Siem Detection (briiirussell/cybersecurity-skills, 413 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Anthropic-Cybersecurity-Skills, which has 34,116 GitHub stars. The repository holds 644 skills in this directory. The repository was last updated on August 31, 2026.
Source: mukul975/Anthropic-Cybersecurity-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.